Experimental Research Lecture Notes PDF

Experimental Research 2 11 25 Lec 11 examy start here  Symbolism for Diagramming Experimental Designs X = exposure of a group to an experimental treatment O = observation or measurement of the dependent variable If multiple observations or measurements are taken, subscript...

Experimental Research 2 11 25 Lec 11 examy start here  Symbolism for Diagramming Experimental Designs X = exposure of a group to an experimental treatment O = observation or measurement of the dependent variable If multiple observations or measurements are taken, subscripts indicate temporal order – I.e., O1, O2, etc. R = random assignment of test units; individuals selected as subjects for the experiment are randomly assigned to the experimental groups RCT vs. Controlled Trial (Quasi Experiments)  Question 2 not requirement butwillmake evidencebetter  Quasi or Pre-Experimental Designs Do not adequately control for the problems associated with loss of external or internal validity bestdesignfor relationship casual True expirement Cannot be classified as true experiments Often used in exploratory research (not causal) Three Examples of Pre-Experimental Designs – One-Shot Design – One-Group Pretest-Posttest Design – Static Group Design  WE 1. One-Shot Design don'thave A.K.A. – after-only design pretestorcontrol group can'tdocausation A single measure is recorded after the treatment is administered wanttojust exploring Study lacks any comparison or control of extraneous influences May be the only viable choice in taste tests Diagrammed as: X O1  2. One-Group Pretest-Posttest Design Subjects in the experimental group are measured before and after the treatment is administered. thetreatment Psstfor No control group nocontrolgroup justpretest posttest Offers comparison of the same individuals before and after the treatment (e.g., training) Diagrammed as O1 X O2  Styoungest 3. Static Group Design Kontrol group A.K.A., after-only design with control group Experimental group is measured after being exposed to the experimental treatment norandomization so notreallytrueexpirement Control group is measured without having been exposed to the experimental treatment No pre-measure is taken Major weakness is lack of assurance that the groups were equal on variables of interest prior to the treatment Diagrammed as: Experimental Group X I AM O1 01 01  Randomized (Pretest-Posttest) Control Group Design A.K.A., Before-After with Control in posttest has True experimental design Experimental group tested before and after treatment exposure Control group tested at same two times without exposure to experimental treatment Includes random assignment to groups Effect of all extraneous variables assumed to be the same on both groups  Posttest-Only Control Group Design ONLYcontrlgroup A.K.A., After-Only with Control True experimental design Experimental group tested after treatment exposure Control group tested at same time without exposure to experimental treatment Includes random assignment to groups Effect of all extraneous variables assumed to be the same on both groups Use in situations when cannot pretest  Posttest-Only Control Group Design Diagrammed as radio – Experimental Group: RX O1 – Control Group: O2 R Effect of the experimental treatment equals (O2 – O1) Example – Assume you manufacture an athlete’s foot remedy – Want to demonstrate your product is better than the competition – Can’t really pretest the effectiveness of the remedy  PETE hewitt Pentship In 1993, Topf and Davis used a posttest-only control group design to examine if CCU (Critical Care Unit) noise affects REM (Rapid Eye Movement) sleep. So they randomly assigned 70 women with no hearing or sleeping problems to attempt to sleep in one of the following conditions: – noisy environment (the subjects listened to an audiotape recording of CCU sounds): treatment group – quiet environment: control group Note that this experiment was done in a sleep laboratory. Their results showed that CCU sounds can cause poorer REM sleep.What can we learn from this example? – The absence of a pretest was justified because participants had no sleeping problems before the experiment.  Randomized Controlled Trials Types Parallel RCT, the patients remain in the same group (i.e., treatment or control group) throughout the study. Crossover RCT means that patients are initially assigned to one group (e.g., the treatment arm) but are switched to the other group (e.g., the placebo arm) during the trial.  Randomization Allocation of treatments to participants is carried out using a chance mechanism so that neither the patient nor the physician know in advance which therapy will be assigned Simplest Case: each patient has the same chance of receiving any of the treatments under study. The opposite is convenience sampling (‘grab’): easily accessed but not random  1. Simple Randomization · Think of tossing a coin each time a subject is eligible to be randomized eachhavesame HEADS: Treatment A opportunity tobe chosen TAILS: Treatment B · Approximately ½ will be assigned to treatments A and B · Randomization usually done using a randomization schedule or a computerized random number generator Maybeunequal so canbebad  3 Problem with Simple Randomization: May result in substantial Pt # Rx. Placebo imbalance in either 1 A – the number of 2 A subjects assigned to 3 B each group 4 A 5 A 6 B Solution: Use blocking and/or stratified randomization 3 2. Block Randomization Example: hadesigns mmmm  Block Randomization The balance based on Pt Randomization the randomization ratio 1 A is achieved within 2 A blocks. 3 B 4 B 5 A In other words, within 6 B each block, subjects 7 A are randomly assigned 8 B to treatment different 9 A groups 10 B 11 B 12 A  3. Stratified Randomized Sampling addedstep Example To ensure balance on an important baseline factor, create strata and set up separate randomization schedules within each stratum Example: if we want prevent an imbalance on age in an osteoporosis study, first create the strata “< 75 years” and “ 75 years” then randomize within each stratum separately Blocking should be also be used within each stratum Stratification  Blinding Masking the identity of the assigned interventions Main goal: avoid potential bias caused by conscious or subconscious factors Open Label: Both investigators and patients are aware of the treatment being given Single blind: patient is blinded Double blind: patient and assessing investigator are blinded Triple blind: committee monitoring response variables (e.g. statistician) is also blinded  Why Should Patients be Blinded? Can Blinding Always be Done? Patients who know they are receiving a new or experimental intervention may report more (or less) side effects. · Patients not on new or experimental treatment may be more (or less) likely to drop out of the study. In some studies, it may be impossible (or unethical) to blind – a treatment may have characteristic side effects – it may be difficult to blind the physician in a surgery or device study Placebo Effect  Are Antidepressants Some just researchers believe that active Placebos antidepressants are not ? effective for the treatment of depression and only outperform placebos due to systematic error. These researchers argue that antidepressants are just active placebos.  Inclusion and Exclusion Criteria Establishing inclusion and exclusion criteria for study participants is a standard, required practice when designing high-quality research protocols. Defining inclusion and exclusion criteria increases the likelihood of producing reliable and reproducible results, minimizes the likelihood of harm to the subjects. Inclusion criteria are characteristics that the prospective subjects must have if they are to be included in the study. Typical inclusion criteria include demographic, clinical, and geographic characteristics such as age, gender, race, ethnicity, marital status, educational experience, language, type of occupation, physical activity, medical conditions, and the presence of medical, or psychosocial,  Inclusion and Exclusion Criteria Establishing inclusion and exclusion criteria for study participants is a standard, required practice when designing high-quality research protocols. Defining inclusion and exclusion criteria increases the likelihood of producing reliable and reproducible results, minimizes the likelihood of harm to the subjects. Inclusion criteria are characteristics that the prospective subjects must have if they are to be included in the study. Typical inclusion criteria include demographic, clinical, and geographic characteristics such as age, gender, race, ethnicity, marital status, educational experience, language, type of occupation, physical activity, medical conditions, and the presence of medical, or psychosocial,  Inclusion and Exclusion Criteria In contrast, exclusion criteria are defined as features of the potential study participants who meet the inclusion criteria but present with additional characteristics that could interfere with the success of the study or increase their risk for an unfavorable outcome. Common exclusion criteria include characteristics of eligible individuals that make them highly likely to be lost to follow-up, miss scheduled appointments to collect data, provide inaccurate data, have comorbidities that could bias the results of the study, or increase their risk for adverse events such as side effects (most relevant in studies testing interventions)  Choosing + study eligibility criteria If criteria are too narrow: Unable to reach recruitment targets Results not generalizable to other important patient populations Recruitment process too complex If criteria are too broad: May include individuals less likely to comply (reducing follow-up) An example: A study of lifestyle-based interventions for counteracting symptoms of menopause might be women between the ages of 45 and 75 who have been diagnosed with menopause. An exclusion criterion for this study might be individuals who meet the inclusion criteria but have abnormal blood tests that + + + Example 2: Factors Influencing Southeastern U.S. Mothers’ Participation in Baby-Friendly Practices: A Mixed-Methods Study